Should drivers cooperate? Performance evaluation of cooperative navigation on simulated road networks using network DEA

Abstract

For drivers, traffic congestion causes enormous delays and increases energy consumption. For a city’s traffic management team, traffic congestion challenges economic growth and increases pollution. Many drivers rely on a GPS navigation system to choose the fastest route to reach their destination. The GPS algorithms generally work for a single driver, while ignoring their collective resulting impact on the road network. If there exists a cooperative centralised routing algorithm that minimises the whole network congestion, the city can greatly benefit from congestion reduction, though some drivers may suffer from such a cooperative routing algorithm. These drivers may opt-out from the cooperative centralised routing, which, in turn, impacts the whole network routing efficiency. So, does having higher proportions of cooperative drivers on the road network always work better? In this paper, we take a heuristic cooperative routing algorithm which minimises the network congestion. We simulate a road network and measure its performance under various proportions of cooperative drivers. We measure both the congestion and the average drivers’ perceived road network performance. Network data envelopment analysis (network DEA) technique is used to see which proportions of cooperative drivers can best benefit the city and drivers collectively.

Keywords:

• Traffic congestion
• cooperative navigation
• network DEA
• performance evaluation

Acknowledgements

The authors would like to thank the anonymous reviewers and the editor for their insightful comments and suggestions in an earlier version of the paper.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research is supported by the University of Massachusetts Lowell seed grant fund for the project titled “Leverage Data Analytics and Game Theory to Study Complex Urban Transportation” (2017–2019), received by two authors, Nichalin S. Summerfield and Amit V. Deokar. This research is supported by National Natural Science Funds of China (No. 71771126, 71801133, 71871105, 71701059), Jiangsu Social Science Fund (17GLB013), Project of Jiangsu Qing Lan and Social Science Excellent Young Scholars. This research is also supported by The Excellent Innovation Teams of Philosophy and Social Science in Jiangsu Province (2017ZSTD022), as well as The Major Research Plan of National Social Science Foundation (18ZDA052).